Regularized PQL for Joint Selection in GLMMs

Performs joint selection in Generalized Linear Mixed Models (GLMMs) using penalized likelihood methods. Specifically, the Penalized Quasi-Likelihood (PQL) is used as a loss function, and penalties are then augmented to perform simultaneous fixed and random effects selection. Regularized PQL avoids the need for integration (or approximations such as the Laplace's method) during the estimation process, and so the full solution path for model selection can be constructed relatively quickly.


Reference manual

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0.8 by Francis Hui, 2 years ago

Browse source code at

Authors: Francis K.C. Hui <[email protected]> , with contributions from Samuel Mueller <[email protected]> and A.H. Welsh <[email protected]>

Documentation:   PDF Manual  

GPL-2 license

Imports gamlss.dist, lme4, Matrix, MASS, mvtnorm, Rcpp

Suggests nlme

Linking to Rcpp, RcppArmadillo

See at CRAN